Modeling and forecasting volatility is essential in trading and risk management. Extensive research has been conducted on volatility modeling in traditional financial markets, and recently, attention has increasingly been directed toward cryptocurrency volatility. The standard approach often relies on econometric models.
Reference [1] applied the GARCH-MIDAS model to study Bitcoin volatility. However, unlike traditional approaches, it introduced two new types of explanatory variables:
- The first is investor attention, measured through Google Trends, social media activity, and news coverage, which reflects market participants’ interest and captures short-term market dynamics in speculative environments.
- The second is uncertainty indices, such as GEPU and GPR, which represent broader macroeconomic and geopolitical risks influencing market stability over longer horizons.
The authors pointed out,
This study highlights the significant role of investor attention and uncertainty indices in modelling Bitcoin volatility using the GARCH-MIDAS framework. Although uncertainty indices are more commonly applied in cryptocurrency volatility analysis, our findings demonstrate that attention indices, such as GTCA, outperform uncertainty indices like GEPU, GPR, and WUI in both explanatory power and forecasting performance. Notably, GTCA is easier to construct and, when developed comprehensively, provides superior insights into Bitcoin volatility dynamics.
Furthermore, an extended analysis of Ethereum, XRP, and BNB (Table 12) confirms that GTCA’s predictive power extends to other major cryptocurrencies, albeit with lower volatility levels compared to Bitcoin.
The two-variable models combining GTCA with GEPU, GPR, or WUI were identified as the most explanatory based on in-sample data and the best-performing according to out-of-sample results. These findings underscore the benefits of integrating GTCA with general uncertainty indices, as the complementary information they provide enhances the accuracy and reliability of Bitcoin volatility predictions.
This study contributes to the literature by being the first to integrate investor attention and uncertainty indices within a unified model for Bitcoin volatility. The construction of the GTCA index using a comprehensive set of search terms ensures robustness and distinguishes this work from prior studies. Additionally, by evaluating both in-sample and out-of-sample performance, this research addresses a critical gap in cryptocurrency volatility forecasting.
In short, the study found that the Google Trends Cryptocurrency Attention (GTCA) index is a significant driver of Bitcoin volatility and successfully integrated it, along with other uncertainty measures, into an effective econometric framework.
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References
[1] Serkan Aras, Mehmet Ozan Ozdemir, Cihan Çılgın, Uncertainty or investor attention: Which has more impact on Bitcoin volatility?, Research in International Business and Finance 77 (2025) 103002
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